论文标题
旨在自我调节AI：金融服务中AI模型治理的挑战和机遇
Towards Self-Regulating AI: Challenges and Opportunities of AI Model Governance in Financial Services
论文作者
论文摘要
AI系统发现了金融服务中的广泛应用领域。他们参与更广泛和日益重要的决策已经升级了对合规性和有效模型治理的需求。当前的治理实践是从更传统的财务应用和建模框架演变而来的。他们经常在AI特征上的根本差异（例如假设中的不确定性）以及缺乏明确的编程中的根本差异。 AI模型治理经常涉及复杂的审查流，并严重依赖手动步骤。结果，它面临着有效性，成本，复杂性和速度的严重挑战。此外，AI模型复杂性的前所未有的增长率提出了有关当前实践可持续性的问题。本文着重于金融服务行业中AI模型治理的挑战。作为展望的一部分，我们提出了一个系统级别的框架，以增加自我调节，以实现鲁棒性和合规性。这种方法旨在通过增加自动化以及监测，管理和缓解功能的整合来实现潜在的解决方案机会。拟议的框架还提供了模型治理和风险管理的提高功能，可以在部署过程中管理模型风险。
AI systems have found a wide range of application areas in financial services. Their involvement in broader and increasingly critical decisions has escalated the need for compliance and effective model governance. Current governance practices have evolved from more traditional financial applications and modeling frameworks. They often struggle with the fundamental differences in AI characteristics such as uncertainty in the assumptions, and the lack of explicit programming. AI model governance frequently involves complex review flows and relies heavily on manual steps. As a result, it faces serious challenges in effectiveness, cost, complexity, and speed. Furthermore, the unprecedented rate of growth in the AI model complexity raises questions on the sustainability of the current practices. This paper focuses on the challenges of AI model governance in the financial services industry. As a part of the outlook, we present a system-level framework towards increased self-regulation for robustness and compliance. This approach aims to enable potential solution opportunities through increased automation and the integration of monitoring, management, and mitigation capabilities. The proposed framework also provides model governance and risk management improved capabilities to manage model risk during deployment.
